The Potency of 4-Methyl-3-Benzoyl Allylthiourea as Anti-Breast Cancer: Molecular Dynamic Simulation, Cytotoxic Activity and its Selectivity Index

Tri Widiandani^1,4*, Delis Susilawati²,Mohammad Rizki Fadhil Pratama³,

Bambang Tri Purwanto^1,4, Siswandono^1,4, Farida Ifadotunnikmah¹

¹Department of Pharmaceutical Sciences, Faculty of Pharmacy,

Universitas Airlangga, Surabaya 60115, Indonesia.

²Master Program of Pharmaceutical Sciences, Faculty of Pharmacy,

Universitas Airlangga, Surabaya 60115, Indonesia.

³Doctoral Program of Pharmaceutical Sciences, Faculty of Pharmacy,

Universitas Airlangga, Surabaya 60115, Indonesia.

⁴Research Group of Drug Development, Faculty of Pharmacy, Universitas Airlangga, Surabaya 60115 Indonesia.

*Corresponding Author E-mail: tri-w@ff.unair.ac.id

ABSTRACT:

Breast cancer is currently one of the most common causes of death in women all over the world. In breast cancer, the proliferation and invasiveness of cancer cells are primarily regulated by hormone receptor-mediated signalling, including estrogen, progesterone, and human epidermal growth factor receptors. The study aims to conduct an in silico investigation using molecular docking and molecular dynamic simulation, as well as to determine the cytotoxicity activity and selectivity index (SI) of 4-methyl-3-benzoyl allylthiourea as an anti-breast cancer agent. Molecular docking was conducted by using the MOE 2022 program to predict the anticancer with three targeted proteins: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). Molecular dynamics simulation was performed by AMBER 20 to investigate the binding affinity of 4-methyl-3-benzoyl allylthiourea on the selected targets with RMSD, RMSF, and MM-GBSA parameters. The cytotoxic activity was performed using the MTT method against T47D and MCF7/HER2 breast cancer cells. The selectivity of the compound was tested by the same method on normal Vero. Results showed the highest binding affinity of 4-methyl-3-benzoyl allylthiourea to ER, followed by PR and HER2 receptors with S scores of -6.287, -7.127, and -6.855 kcal/mol, respectively. The molecular dynamics simulation showed that interaction between 4-methyl-3-benzoyl allylthiourea and 1E3K is predicted to be the most stable conformation than other receptors. The cytotoxicity test resulted in IC₅₀ in T47D and MCF7/HER2 cells of 296 and 134 µM, respectively. The SI values of 4-methyl-3-benzoyl allylthiourea for T47D and MCF7/HER2 are 2 and 4, respectively. In conclusion, 4-methyl-3-benzoyl allylthiourea has high potential as an anti-breast cancer candidate that acts on the ER, PR, and HER2 receptors. Therefore, it is very promising for further development.

KEYWORDS: Breast cancer, 4-methyl-3-benzoyl allylthiourea, molecular dynamics simulation, selectivity index, T47D, MCF7/HER2.

INTRODUCTION:

Cancer is one of the chronic diseases that is on the rise today. Globally, cancer is one of the leading causes of death, with 19.3 million new cases and 10 million deaths expected by 2020.¹ Female breast cancer has become the most commonly diagnosed cancer among women, with an estimated 2.3 million new cases diagnosed in 2020¹. In breast cancer, the proliferation and invasiveness of cancer cells are regulated mainly by hormone receptor-mediated signalling, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 receptor (HER2). In the case of breast cancer, 50% of cases are caused by excessive expression of estrogen protein, and 30% of cases are caused by HER-2 expression with poor prognosis.^2,3,4 The medication used to treat metastatic or advanced breast cancer is lapatinib.⁵ It works by blocking the abnormal protein action that instructs cancer cells to proliferate, assisting in preventing or reducing cancer cell growth.⁶ However, long-term use of lapatinib can cause resistance to the drug.⁷

The thiourea derivative, allylthiourea, is one of the promising anticancer groups to be further developed. This derivative acts as an EGFR inhibitor by inhibiting the intracellular region's tyrosine kinase receptors (RTKs).⁸ Recently, allylthiourea has been developed as an anticancer by modifying the structure of thiourea. A previous study showed that the derivatives with pharmacophore thiourea (-HN-C (= S) -NH-) showed antitumor activity against mammary and colon carcinoma cells.⁹ Furthermore, our group also has demonstrated the derivatives of 3-benzoyl allylthiourea showing high cytotoxic activity in breast cancer cells MCF-7.¹⁰

In this study, an in silico approach was performed to predict the anticancer properties of allylthiourea and its derivatives, 3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea, which is indicated by the energy value of the ligand-receptor interaction bond using the molecular operating environment (MOE) program.^11,12 The molecular docking and molecular dynamic were conducted on the three targeted proteins ER, PR, and HER-2, followed by molecular dynamic simulation. This study also determined the anti-proliferation activity of 4-methyl-3-benzoyl allylthiourea and 3-benzoyl allylthiourea, its parent compounds. This investigation uses the human breast cancer cell line T47D, MCF-7/HER2, as well as the normal cell line Vero using the MTT test method. Further selectivity is calculated using the selectivity index (SI), which compares each compound's CC₅₀ and IC₅₀ values of each compound in normal and cancer cells.

MATERIALS AND METHODS:

Materials:

Instruments and materials:

The instruments used were hardware and software. The software used were Discovery Studio 2021, MOE 2022 for an academic license (K22CCG679), AMBER 20, and websites such as Protein Data Bank (https://www.rcsb.org/), pkCSM (https://biosig.lab.uq.edu.au/pkcsm/), and PDBsum (http://www.ebi.ac.uk/pdbsum/). Meanwhile, the hardware used were laptop 11^th Gen Intel® Core™ i3-1115G4 RAM 4 GB (Discovery studio 2021 and MOE 2022) and CPU 12^th Gen Intel® Core™ i9-12900F RAM 32 GB (AMBER 20). The materials used in this study were the structures and the compounds of allylthiourea, 3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea (Figure 1), estrogen receptor (PDB ID: 3ERT), progesterone receptor (PDB ID: 1E3K) and HER2 receptor (PDB ID: 3PP0), and lapatinib as reference drug.

Chemical Material:

3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea were synthesized and the structure was confirmed with proton and carbon NMR and HR-MS as described in our previous study.¹³Lapatinib was obtained from Sigma.

Target receptor identification:

Identification and analysis of target receptors were carried out by Ramachandran plot with the PDB ID 3ERT, 1E3K, and 3PP0 at https://biosig.lab.uq.edu.au/pkcsm/.

Molecular docking:

Molecular docking calculations were performed using the molecular operating environment (MOE) on three targeted proteins: ER, PR, and HER-2. The structures of each target were downloaded as a PDB file from Protein Data Bank database. The compounds were docked to the active sites of each enzyme. The method was validated by redocking the native ligand against the receptor's binding site, which is deemed valid if the root mean square deviation (RMSD) value is ≤2Å.^14-17 In addition, molecular docking was applied in the following research to find the optimum configuration between ligands and receptors. The ligands with the Highest binding affinity energy would be chosen for further molecular dynamics simulation.¹⁸

Molecular Dynamics:

Molecular dynamics simulation used AMBER 20 and it was carried out on all receptors with the highest binding affinity energy on molecular docking result. The molecular dynamics simulation begins with the ligand parameterization step by adding the ff14SB force field. The next step was determining the system’s initial coordinate point and minimizing it by adding ions and solvation. Then, the system equilibration was carried out through a gradual heating of 0 to 310 K, which is accompanied by a decrease in resistance and a constant change of resistance for 100 ns.¹⁸

Cell Culture:

The in vitro cytotoxic activity studies were carried out using breast cancer and non-cancerous cell lines. The T47D (estrogen and progesterone-positive human breast cancer) and MCF-7/HER-2 (HER2-positive human breast cancer) as well as Vero cells were collected from the Faculty of Pharmacy, Airlangga University, and the Faculty of Medicine, Gadjah Mada University. Cells were cultured in RPMI 1640 or M199 medium containing 10% FBS, 1% Amphotericin-B, and 1% Pen-Strep.^19,20

Anticancer activity and cytotoxicity test

The cytotoxic assay was performed using the MTT method against T47D, MCF-7/HER-2, and Vero cells. Cells were seeded on 96-well plates with a cell density of 5x10³ cells/well and incubated at 5% CO₂ at of 37°C for 24 hours. 100 µL of the sample was added into each well and then incubated for 24 hours. After that, 0.5 mg/ µL of MTT reagent was added to each well. Cells were then incubated for 3-4 hours until the crystal was formed. The reaction was stopped with 10% SDS in 0.01 N HCl. Absorbance was read with a microplate reader at λ=570 nm.^19,21-26

Selectivity Index (SI)

The selectivity index is a comparison of the CC₅₀ value of a test compound in normal cells compared to the IC₅₀ of the same test composition in cancer cells.²¹

RESULT:

Target receptor identification

The Ramachandran plot was used to analyse the stability of proteins and visualize the three-dimensional coordinates. The amino acid was found in the red regions, which represent the most favoured regions: the brown regions represent additional allowed regions, and the yellow regions represent generously allowed regions¹⁷ (Table 1).

Table 1. Ramachandran plot for all receptors

PDB ID	Most Favoured Regions (%)	Disallowed Regions (%)
3ERT	91.2	0.0
1E3K	84.6	0.4
3PP0	90.3	0.4

Molecular docking

The molecular docking method has been validated by redocking the native ligand and its active binding site. The RMSD values for all receptors are less than 2A, suggesting its validity for molecular docking analysis (Table 2). The compounds was docked include allylthiourea, 3-benzoyl allylthiourea, and 4-methyl-3-benzoyl allylthiourea.

Table 2. The result of docking validation

Native Ligand	PDB ID	RMSD (A)	S (kcal/mol)
4-Hydroxytamoxifen	3ERT	0.173	-9.852
Metribolone	1E3K	0.400	-11.837
SYR127063	3PP0	1.064	-10.209

(a)

(b)

(c)

Figure 1. The structure of allylthiourea (a), 3-benzoyl allylthiourea (b), and 4-methyl-3-benzoyl allylthiourea (c)

Table 3. The binding affinity energy values on molecular docking for compounds with receptors 3ERT, 1E3K, and 3PP0.

PDB ID	Compound	S (kcal/mol)	Amino Acid Interaction
PDB ID	Compound	S (kcal/mol)	Hydrogen Bonds	Hydrophobic Bonds
3ERT	Allylthiourea	-4.103	Thr347	Met528, His524, Ala350, Leu387, Leu384,
	3-benzoyl allylthiourea	-5.967	Thr347, Met343	Met421, Glu419, Gly420, Ile424, Gly521, Leu384, Met388, Arg394, Glu353, Leu349, Leu346, Phe 404, Met528, Leu525
	4-methyl-3-benzoyl allylthiourea	-6.287	Thr347	Met343, Met528, Leu525, Gly521, Gly420, Ile424, Met421, Glu419, Met388, Glu353, Arg394, Leu349, Phe404, Leu346
1E3K	Allylthiourea	-4.661	Leu887, Met756	Tyr890, Asn719, Met909, Thr894, Leu718, Leu715, Leu797, Met801
	3-benzoyl allylthiourea	-6.717	Met756	Leu887, Tyr890, Thr894, Asn719, Leu715, Leu718, Met801, Leu763, Arg766, Gln725, Met759, Val760
	4-methyl-3-benzoyl allylthiourea	-7.127	Leu887	Tyr890, Phe905, Val903, Thr894, Asn719, Cys891, Met801, Val760, Arg766, Gln725, Phe794, Met756, Leu797
3PP0	Allylthiourea	-4.796	Ser783	Met774, Phe864, Thr862, Ile752, Val797, Thr798, Leu796, Leu785
	3-benzoyl allylthiourea	-6.591	Thr862, Asp863	Thr798, Ser783, Arg784, Ala771, Glu770, Lys753, Ile752, Al751, Leu726, Cys805
	4-methyl-3-benzoyl allylthiourea	-6.855	Met801	Leu800, Gly804, Leu852, Thr862, Asp863, Leu785, Val797, Thr798, Ile752

Figure 2. 3D and 2D visualization of 4-methyl-3-benzoyl allylthiourea with a) 3ERT, b) 1E3K, c) 3PP0 interactions

Figure 3. a) RMSD analysis of 4-methyl-3-benzoyl allylthiourea with 3ERT, 1E3K, and 3PP0 (overlay), as well as RMSF analysis of 4-methyl-3-benzoyl allylthiourea with b) 3ERT, c) 1E3K, d) 3PP0

Molecular dynamics simulation:

Root Mean Square Deviation (RMSD):

The RMSD method predicts the time required for a compound to reach a stable conformation on the active site of the receptor and compares between the position and distance of the ligand to the active site of the receptor after production and before production.

Root Mean Square Fluctuation (RMSF):

RMSF predicts amino acid flexibility by analysing their fluctuations during molecular dynamics simulations. Low flexibility amino acid residues have low fluctuations, indicating more stable bonding interaction and predicting the residues have a role to play at the active site of ligand-receptor binding. Meanwhile, amino acids with high flexibility have substantial fluctuations, indicating less stable bond interaction due to their positions varying frequently during the molecular dynamic simulation. Results showed the low fluctuation of 4-methyl-3-benzoyl allylthiourea with 3ERT, 1E3K and 3PP0 receptors are Leu448, Lys822 and Ile128, respectively.

Molecular Mechanics-Generalized Born Surface Area (MM-GBSA):

MM-GBSA (Molecular Mechanics Generalised Born Surface Area) calculates the Gibbs free energy (∆G) of the bond interaction between the ligand and the receptor in a molecular dynamics simulation system. Gibbs free energy is the produced when the receptor and ligand engage and form a bond. This ∆G value can be used to measure the affinity of ligand binding at the receptor active site; the lower the ∆G value, the higher the binding affinity. Based on the result (Table 4), the interaction between 4-methyl-3-benzoyl allylthiourea and 1E3K is predicted to be the most stable conformation of other receptors.

Table 4. The bond energy calculation of MM-GBSA

Energy component	3ERT (kcal/mol)	3PP0 (kcal/mol)	1E3K (kcal/mol)
Van der Waals energy (VDWAALS)	-29.925	-2.989	-35.226
Electrostatic energy (EEL)	107.019	-30.552	-30.411
MMGBSA polar solvation energy (EGB)	-90.735	32.736	40.535
MMGBSA non-polar solvation energy (ESURF)	-4.375	-0.472	-5.058
ΔG_gas (VdW + EEL)	77.094	-33.542	-70.011
ΔG_solv (EGB + ESURF)	-95.111	32.263	35.476
ΔG_TOTAL (VdW + EEL + EGB + ESURF)	-18.016	-1.279	-30.16

Cytotoxicity Activity:

(c)

Cell viability is obtained by converting the absorption values of formations formed due to the transfer of MTT reagents. Model curves of the relationship between the concentration vs viability of T47D, MCF-7/HER-2, and Vero cells of the 4-methyl-3-benzoyl allylthiourea and 3-benzoyl allylthiourea compounds were shown in Figure 4. Both 3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea suppressed the cell viability in a dose-dependent manner on T47D and MCF7/HER2 cell lines with three replications.

DISCUSSIONS:

To discover a new drug against human breast cancer, molecular modelling of the human ER, PR, and HER-2 was performed and validated based on Ramachandran plot. In this analysis, the receptor is considered good if it has more than 90% of the most favoured regions and less than 15% disallowed.^28-30 The result shows that the most favoured regions for 3ERT, 1E3K and 3PP0 are 91.2%, 84.6%, 90.3%, respectively. 1E3K has less than 90% of most favoured regions. However, both receptors have a good disallowed region. Therefore, all the receptors could be used for the molecular docking method. Additionally, all of receptors has been validated by redocking the native ligand and have less than 2Å. Therefore, all the receptor was valid and could be used for the molecular docking simulation.

The strength of the ligand and its receptor interaction depends on the binding affinity. Ligands with the lowest binding free energy have a stable interaction with the receptor. Our computational docking study showed that 4-methyl-3-benzoyl allylthiourea have a highest greater binding affinity energy on 3ERT, 1E3K, and 3PP0 receptors with the S value of -6.287, -7.127, -6.855 kcal/mol, respectively (Table 2). Thus, 4-methylbenzoyl-3-allylthiourea was applied for the molecular dynamic simulation.

Hydrogen bonds and hydrophobic bonds were examined in ligands and receptors. Hydrogen bonds are bonds of elements (F, O, and N) with hydrogen atoms. It is a form of electrostatic interaction of hydrogen that binds to other electronegative atoms and the most potent dipole-dipole force.²⁷ In addition to hydrogen bonds, hydrophobic bonds also contribute to biological activity. Hydrophobic bonds minimize contact between nonpolar residues and water. Hydrophobic interactions can enhance the interaction between ligands and receptors. Our study showed that 4-methyl-3-benzoyl allylthiourea has at least one similar residue on the hydrogen and hydrophobic bonds with the main compound (Figure 2). Furthermore, 4-methyl-3-benzoyl allylthiourea has the most stable conformation with 1E3K from the beginning to the end of the simulation with 1.761Å of the average RMSD value (Figure 3). The interaction of 4-methyl-3-benzoyl allylthiourea with 3ERT and 3PP0 receptors fluctuated slightly at 20 to 30 ns, then had a stable conformation until the end of the simulation with the average RMSD value 2.712Å and 2.383Å, respectively.

The in vitro study demonstrated that 3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea have anticancer activity by dose-dependent suppression on the viability of T47D and MCF7/HER2 (Figure 4). This anticancer activity is selective to the mammary cancer cell lines, which is shown by high SI value of 3 to 5 and 2 to 5 for 3-benzoyl allylthiourea and 4-methyl-3-benzoyl allylthiourea, respectively (Table 5). Generally, higher SI ratios indicate greater efficacy and safety of a drug. A previous study demonstrated that a compound is said to be selective when it has an SI value of ≥3.17. Furthermore, Nogueira and Rosário have submitted a lower SI value of ≥2 to be said to be a bioactive but non-toxic compound with an SI value of <1 that is potentially toxic to normal cells. Based on these criteria, the 4-methyl-3-benzoyl allylthiourea compound has potential as an anti-cancer compound in T47D and MCF7/FER2 cells and is selective to normal Vero cells.^31-33

ACKNOWLEDGMENTS:

Thank you for the research facilities at the In Vitro-1 Laboratory Research Centre and Computing Laboratory in the Research Group of Drug Development, Faculty of Pharmacy Universitas Airlangga. This research is also supported by the Directorate of Research and Community Service Ministry of Education, Culture, Research, and Technology Republic of Indonesia through the PDUPT scheme, 2020-2021.

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

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Received on 22.02.2024 Revised on 15.07.2024

Accepted on 19.10.2024 Published on 27.03.2025

Available online from March 27, 2025

Research J. Pharmacy and Technology. 2025;18(3):1182-1188.

DOI: 10.52711/0974-360X.2025.00171

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Compounds	IC₅₀ (µM)		CC₅₀(µM)	SI
Compounds	T47D	MCF7/HER2	Vero	Vero : T47D	Vero : MCF7/HER2
3-benzoyl allylthiourea	633±2.16	640±3.70	3.350±3.35	5	3
4-methyl-3-benzoyl allylthiourea	296±3.59	134±5.35	579±4.19	2	5
Lapatinib	34±0.98	81±2.49	-	-	-